Azure Data Engineer
Gurugram, Haryana, India
- Experience
- 6–8 years
- Employment
- Full-time
- Work mode
- Onsite
- Salary
- ₹10 L–15 L / year
- Deadline
- Apply by 1 Nov 2026
- Posted
- 2025-02-28
Required skills
| Skill | Experience | Level |
|---|---|---|
| Azure | 5+ years | Intermediate |
| Azure DataBricks | Not specified | Not specified |
| PySpark | Not specified | Not specified |
| Azure Data Factory | Not specified | Not specified |
About the role
Azure Data Engineer
Candidate Skills and Qualifications:
• Experience: 6 to 8+ years as an Azure Data Engineer, with a strong focus on Azure Databricks and PySpark.
• Data Pipeline Development: Proven expertise in designing, developing and maintaining complex data pipelines on Azure platforms.
• Data Migration: Experience in migrating data from on-premises and cloud-based systems to Azure, ensuring seamless data integration.
• Data Modeling: Proficient in dimensional data modeling and designing data warehouses for efficient data storage and retrieval.
• Azure Services Proficiency: Hands-on experience with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake and Azure SQL Database.
• Programming Skills: Strong proficiency in Python and SQL; familiarity with Scala is advantageous.
• Big Data Frameworks: Experience with big data frameworks, particularly Apache Spark, for large-scale data processing.
• Version Control and CI/CD: Familiarity with Azure DevOps, Git and implementing CI/CD pipelines for automated deployments.
• Security Practices: Knowledge of Azure security practices, including Azure Active Directory (AAD), Key Vault and Role-Based Access Control (RBAC).
Role & Responsibilities
• Data Pipeline Management: Design, develop and maintain complex data pipelines on Azure to support business requirements.
• Data Migration: Migrate data from on-premises and cloud-based systems to Azure platforms, ensuring data integrity and security.• Data Modeling and Warehousing: Implement and optimize dimensional data models and data warehouses for scalable and efficient data processing.
• Azure Services Utilization: Work extensively with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake and Azure SQL Database to manage and process large datasets.
• Programming: Write efficient and scalable code using Python and SQL to support data engineering workflows.
• ETL/ELT Processes: Develop and maintain ETL/ELT processes, leveraging big data frameworks such as Apache Spark for large-scale data processing.
• CI/CD Implementation: Set up and manage Azure DevOps pipelines, Git repositories and CI/CD processes for seamless deployment and automation.
• Security Compliance: Ensure compliance with Azure security best practices, including implementing AAD, Key Vault and RBAC for secure data access.
• Collaboration: Collaborate with cross-functional teams to identify, develop and implement data solutions to meet organizational needs.
• Monitoring and Troubleshooting: Monitor and troubleshoot data workflows, ensuring high performance and reliability.
Preferred Candidate Profile
• Experience: Minimum of 5 years as an Azure Data Engineer.
• Certifications: At least one relevant certification, such as the Microsoft
Certified: Azure Data Engineer Associate.
• Azure Data Services: In-depth knowledge of Azure data services, including Data Factory, Databricks, Synapse Analytics, Data Lake and SQL Database.
• Programming Skills: Strong programming skills in Python and SQL; familiarity with Scala is a plus.
• Data Modeling and ETL: Expertise in data modeling and ETL/ELT processes.• Big Data Frameworks: Hands-on experience with big data frameworks, such as Apache Spark.
• Version Control and CI/CD: Familiarity with Azure DevOps, Git and CI/CD implementation.
• Security Practices: Understanding of Azure security practices, including Azure Active Directory (AAD), Key Vault and Role-Based Access Control (RBAC).
• Analytical Skills: Strong analytical and problem-solving abilities.
• Communication: Excellent communication and teamwork skills.
• Adaptability: Ability to adapt to changing business needs and work effectively in an offshore setup.